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Tiny machine learning (TinyML) has become an emerging field according to the rapid growth in the area of the internet of things (IoT). However, most deep learning algorithms are too complex, require a lot of memory to store data, and consume an enormous amount of energy for calculation/data movement; therefore, the algorithms are not suitable for IoT devices such as various sensors and imaging systems. Furthermore, typical hardware accelerators cannot be embedded in these resource-constrained edge devices, and they are difficult to drive real-time inference processing as well. To perform the real-time processing on these battery-operated devices, deep learning models should be compact and hardware-optimized, and hardware accelerator designs also have to be lightweight and consume extremely low energy. Therefore, we present an optimized network model through model simplification and compression for the hardware to be implemented, and propose a hardware architecture for a lightweight and energy-efficient deep learning accelerator. The experimental results demonstrate that our optimized model successfully performs object detection, and the proposed hardware design achieves 1.25× and 4.27× smaller logic and BRAM size, respectively, and its energy consumption is approximately 10.37× lower than previous similar works with 43.95 fps as a real-time process under an operating frequency of 100 MHz on a Xilinx ZC702 FPGA.

Though custom deep learning (DL) hardware accelerators are attractive for making inferences in edge computing devices, their design and implementation remain a challenge. Open-source frameworks exist for exploring DL hardware accelerators. Gemmini is an open-source systolic array generator for agile DL accelerator exploration. This paper details the hardware/software components generated using Gemmini. The general matrix-to-matrix multiplication (GEMM) of different dataflow options, including output/weight stationary (OS/WS), was explored in Gemmini to estimate the performance relative to a CPU implementation. The Gemmini hardware was implemented on an FPGA device to explore the effect of several accelerator parameters, including array size, memory capacity, and the CPU/hardware image-to-column (im2col) module, on metrics such as the area, frequency, and power. This work revealed that regarding the performance, the WS dataflow offered a speedup of 3× relative to the OS dataflow, and the hardware im2col operation offered a speedup of 1.1× relative to the operation on the CPU. For hardware resources, an increase in the array size by a factor of 2 led to an increase in both the area and power by a factor of 3.3, and the im2col module led to an increase in area and power by factors of 1.01 and 1.06, respectively.

This study investigates how different types of corporate environmental practices affect environmental performance. This paper is theoretically anchored in the natural resource-based view and, methodologically, it applies the recently recommended disaggregated approach in a new effort to deepen our understanding of how environmental performance is associated with different types of corporate environmental practices. The results partially affirm the argument of the natural resource-based view that proactive corporate environmental practice leads to better environmental performance, whereas reactive corporate environmental practice is associated with worse environmental performance. However, the relationship between corporate environmental practices and environmental performance should be carefully interpreted, because the findings differ depending on how Kinder Lydenberg Domini (KLD) strength and concern rating scores are measured. The results further demonstrate that the disaggregate KLD environmental rating scores can be better alternative measures for corporate environmental practices than the commonly used composite and aggregate KLD rating scores, given that disaggregate KLD concern and strength scores represent independent rather than similar constructs. The findings are expected to help both theorists and practitioners achieve a more nuanced understanding of the measurement of environmental practices.

Autophagy is essential for cell survival and cellular homeostasis under various stress conditions. Therefore, autophagy dysfunction is associated with the pathogenesis of various human diseases. We explored the regulatory role of RhoBTB3 in autophagy and its interaction with activating molecules in AMBRA1. RhoBTB3 deficiency was found to induce autophagy, while its overexpression inhibited autophagy induction. Through immunoprecipitation and mass spectrometry, AMBRA1 was identified as a substrate of RhoBTB3. The study revealed that RhoBTB3 regulates AMBRA1 stability by influencing its protein levels without affecting its mRNA levels. RhoBTB3 induced the ubiquitination of AMBRA1, leading to proteasome-mediated degradation, with the ubiquitination occurring at K45 on AMBRA1 through a K27-linked ubiquitin chain. The knockdown of AMBRA1 blocked RhoBTB3 knockdown-induced autophagy, indicating the dependency of autophagy on AMBRA1. Thus, RhoBTB3 negatively regulates autophagy by mediating AMBRA1 ubiquitination and degradation, suggesting RhoBTB3 as a potential therapeutic target for autophagy-related diseases.

Because drowsy driving increases the incidence of traffic accidents and leads to fatal accidents, a lot of social attention is needed. The number of accidents by drowsy drivers increases every year. So various studies have been performed to solve the issue all over the world. Among others, we focus on the non-contact method. Various vibration signals such as engine, tire, and body vibration are generated in a driving or stationary car. The existing static system is used to measure microscopic vibrations generated from the drivers breathing and heartbeat. It is necessary to design a structure that can cushion vehicle vibration through an advanced signal processing program. In this study, actual vehicles test was conducted to analyze the transmission characteristics of fine vibration through the change of plate structure under sensors. The plate structure is a urethane structure plate that can cushion vehicle vibration while driving. Furthermore, we developed an AI algorithm that classifies whether a subject is in a sleep state or not using a piezoelectric sensor-based BCG signal. This paper shows the AI method is more accurate than the method of classifying sleep states according to analyzing HRV and the ratio of LF/HF with ECG signal. In order to train the system, the subject's biosignals were acquired every 30 s, and 797 data were comparatively analyzed.

In this paper, we optimized Number Theoretic Transform (NTT) and random sampling operations on low-end 8-bit AVR microcontrollers. We focused on the optimized modular multiplication with secure countermeasure (i.e., constant timing), which ensures high performance and prevents timing attack and simple power analysis. In particular, we presented combined Look-Up Table (LUT)-based fast reduction techniques in a regular fashion. This novel approach only requires two times of LUT access to perform the whole modular reduction routine. The implementation is carefully written in assembly language, which reduces the number of memory access and function call routines. With LUT-based optimization techniques, proposed NTT implementations outperform the previous best results by 9.0% and 14.6% for 128-bit security level and 256-bit security level, respectively. Furthermore, we adopted the most optimized AES software implementation to improve the performance of pseudo random number generation for random sampling operation. The encryption of AES-256 counter (CTR) mode used for random number generator requires only 3184 clock cycles for 128-bit data input, which is 9.5% faster than previous state-of-art results. Finally, proposed methods are applied to the whole process of Ring-LWE key scheduling and encryption operations, which require only 524,211 and 659,603 clock cycles for 128-bit security level, respectively. For the key generation of 256-bit security level, 1,325,171 and 1,775,475 clock cycles are required for H/W and S/W AES-based implementations, respectively. For the encryption of 256-bit security level, 1,430,601 and 2,042,474 clock cycles are required for H/W and S/W AES-based implementations, respectively.

In this study, self-healing hydrogels were created using oxidized hydroxybutanoyl glycan (OHbG) and quaternized carboxymethyl chitosan (QCMCS), displaying antioxidant and antibacterial properties for pH-responsive drug delivery. The structures of the modified polysaccharides were confirmed through 1H NMR analysis. Double crosslinking in the hydrogel occurred via imine bonds (between the aldehyde group of OHbG and the amine group of QCMCS) and ionic interactions (between the carboxyl group of OHbG and the quaternized group of QCMCS). The hydrogel exhibited self-healing properties and improved thermal stability with an increase in OHbG concentration. The OHbG/QCMCS hydrogel demonstrated high compressive strength, significant swelling, and large pore size. Drug release profiles varied between pH 2.0 (96.57%) and pH 7.4 (63.22%). Additionally, the hydrogel displayed antioxidant and antibacterial effects without compromising the polysaccharides’ inherent characteristics. No cytotoxicity was observed in any hydrogel samples. These findings indicate that the OHbG/QCMCS hydrogel is a biocompatible and stimuli-responsive drug carrier, with potential for various pharmaceutical, biomedical, and biotechnological applications.

Seaweeds are thought to be promising candidates for functional foods and to help prevent thrombotic and related cardiovascular diseases. Codium fragile (Suringer) Hariot has been traditionally used as a culinary ingredient, and it possesses a range of biological activities, including the inhibition of platelet function. However, the mechanism of this inhibition is unclear. The aim of this study was to examine the inhibitory effect of C. fragile in platelet function. The antiplatelet activity of C. fragile on agonist-activated platelet aggregation, granule secretion, calcium mobilization, platelet spreading, and clot retraction was assessed. The phosphorylation of c-Src, Syk, PLCγ2, and several proteins involving in the αIIbβ3 integrin outside-in signaling pathway were also studied in thrombin and CRP-stimulated platelets. The antithrombotic effect was investigated in mice using ferric chloride-induced arterial thrombus formation in vivo . Transection tail bleeding time was used to evaluate whether C. fragile inhibited primary hemostasis. The main components and contents of C. fragile ethanol extract were confirmed by GC-MS analysis. C. fragile significantly impaired agonist-induced platelet aggregation granule secretion, calcium mobilization, platelet spreading, and clot retraction. Biochemical analysis revealed that C. fragile inhibited the agonist-induced activation of c-Src, Syk, and PLCγ2, as well as the phosphorylation of PI3K, AKT, and mitogen-activated protein kinases (MAPKs). The inhibitory effect of C. fragile resulted from an inhibition of platelet αIIbβ3 integrin outside-in signal transduction during cell activation. Oral administration of C. fragile efficiently blocked FeCl 3 -induced arterial thrombus formation in vivo without prolonging bleeding time. GC-MS analysis revealed that phytol was the main constituent and the total content of isomers was 160.8 mg/kg. Our results demonstrated that C. fragile suppresses not only the inside-out signaling of αIIbβ3 integrin but also outside-in signal transmission. Therefore, C. fragile could be an effective antiplatelet therapeutic candidate.

The conventional recycling processes for waste sand with inorganic binder (WSIB) in aluminum alloy casting involve washing, heat treatment, and mechanical grinding. However, this process is complex and inefficient for removing the residual binder on the surface of WSIB. This study proposes a simplified and effective recycling process using ultrasound treatment to more efficiently remove residual binder on the surface of WSIB. To evaluate its effectiveness, we characterized ultrasonically recycled sand (URS), conventionally recycled sand (CRS), and virgin sand (VS). The evaluation consisted of the following three steps: (1) characteristics of sand, such as residual binder content, particle size distribution, surface morphology, and specific surface area; (2) measuring the properties of sand cores, including bending strength and the volume of gas evolved during the pouring of A356 Al melts; and (3) measurement of porosity level at the interface between the sand core and A356 Al castings. These results indicate that the ultrasonic recycling process can achieve a technically efficient and simplified recycling process for WSIB.